R Notebook

load("/lustre/scratch117/cellgen/team218/gp7/Joe/Jupyter/PAGA.rda")

cannot open compressed file '/lustre/scratch117/cellgen/team218/gp7/Joe/Jupyter/PAGA.rda', probable reason 'No such file or directory'Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection

load("/lustre/scratch117/cellgen/team218/gp7/Joe/Jupyter/PAGA.rda")

cannot open compressed file '/lustre/scratch117/cellgen/team218/gp7/Joe/Jupyter/PAGA.rda', probable reason 'No such file or directory'Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection

library(data.table)

Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
data.table 1.14.0 using 30 threads (see ?getDTthreads).  Latest news: r-datatable.com

Attaching package: ‘data.table’

The following object is masked _by_ ‘.GlobalEnv’:

    .N

library(tseries)

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

    ‘tseries’ version: 0.10-48

    ‘tseries’ is a package for time series analysis and computational finance.

    See ‘library(help="tseries")’ for details.

library(ggplot2)

PAGA_graph_connectivities <- read.matrix("/lustre/scratch117/cellgen/team218/gp7/Joe/PAGA", header = T, sep = ",")

cannot open file '/lustre/scratch117/cellgen/team218/gp7/Joe/PAGA': No such file or directoryError in count.fields(file, sep = sep, skip = skip) : 
  cannot open the connection

save(/lustre/scratch117/cellgen/team218/gp7/Joe/PAGA/)

node = "9:67029664-67029742"


ggplot() +
  geom_point(data=PAGA, aes(FA1, FA2), colour="grey", alpha=0.05) +
  geom_point(data=pseudopool_matrix.PAGA[Coord==node, ], aes(FA1, FA2, colour=PSI, size=log(SN_Reads) ), alpha=0.5 ) +
   scale_colour_gradient2(low = "steelblue", midpoint = 0.5, mid = "lightskyblue3", high = "firebrick", na.value = "gray40") +
  theme_bw() +
  theme(legend.position = "top")

PAGA_graph_connectivities.melted$value <- as.numeric(as.character(PAGA_graph_connectivities.melted$value))

PAGA_graph_connectivities.melted[value==0, ]

is.data.table(PAGA_graph_connectivities.melted)

node="15:77091812-77091854"

edges <- merge(PAGA_net[ , .(Var1=as.character(Var1), Var2=as.character(Var2), value)], vert, by.x='Var1', by.y='cluster')

Error in is.data.table(y) : object 'vert' not found

layout.fruchterman.reingold

function (..., params = list()) 
{
    do_call(layout_with_fr, .args = c(list(...), params))
}
<bytecode: 0x55e467194978>
<environment: namespace:igraph>

General view

Warning message:
In readChar(file, size, TRUE) : truncating string with embedded nuls

ggplot(pseudopool_matrix.zscore.PAGA[Coord==node, ]) +
        geom_point(aes(FA1, FA2, colour=cluster, size=log(n_cells)), position = position_jitter(w = 3e3, h = 3e3), alpha=0.5 ) +
                theme_bw() +
     #scale_colour_gradient2(low = "steelblue", midpoint = 0.5, mid = "lightskyblue3", high = "firebrick", na.value = "gray40") +
        theme(legend.position = "none") 

library("ggrepel")

ggplot() +
  
        geom_point(data=PAGA, aes(FA1, FA2, colour=batch), alpha=0.2) +
  #      geom_point(data=pseudopool_matrix.zscore.PAGA[Coord==node, ], aes(FA1, FA2, colour=PSI, size=log(n_cells)), position = position_jitter(w = 2e3, h = 2e3), alpha=0.5 ) +
                theme_bw() +
  #   scale_colour_gradient2(low = "steelblue", midpoint = 0.5, mid = "lightskyblue3", high = "firebrick", na.value = "gray40") +
        theme(legend.position = "top") 

total_genes.gene_table <- data.table(getBM(attributes=c('ensembl_gene_id', "mgi_symbol"),filters = 'ensembl_gene_id', values = total_genes , mart = ensembl_mm))

Error in getBM(attributes = c("ensembl_gene_id", "mgi_symbol"), filters = "ensembl_gene_id",  : 
  object 'total_genes' not found

#Good
#Elavl2
#Msi1

#Bad
#Ptbp2

gene_vector <- c("Mbnl1", "Elavl2", "Rbfox2", "Rbm24", "Msi1", "Esrp1")
#gene_vector <- c("Elavl2", "Celf4", "Msi1", "Srrm4", "Elavl3", "Elavl1")


#gene_vector <- c("Mbnl1", "Ptbp2", "Rbfox2", "Rbm24", "Ptbp3", "Esrp1")

PAGA.genes <- merge( gene_count[mgi_symbol %in%  gene_vector,] , PAGA[ ,.(cell=V1, FA1, FA2)], by="cell", all.y=T  )

#PAGA.genes$cell <- factor( PAGA.genes$cell, levels= PAGA.genes[order(TpM)]$cell)


ggplot() +
        geom_point(data=PAGA, aes(FA1, FA2), color="lightgray", alpha=0.1) +  
        geom_point(data=PAGA.genes[!is.na(mgi_symbol) & !is.na(TpM), ][order(TpM)], aes(FA1, FA2, colour=log10(TpM)), alpha=0.2) +
  #      geom_point(data=pseudopool_matrix.zscore.PAGA[Coord==node, ], aes(FA1, FA2, colour=PSI, size=log(n_cells)), position = position_jitter(w = 2e3, h = 2e3), alpha=0.5 ) +
  
  facet_wrap(. ~ mgi_symbol, ncol=2) +
                theme_classic() +
     scale_colour_gradient2(low = "steelblue", midpoint = 2, mid = "lightskyblue3", high = "firebrick", na.value = "gray40", limits=c(0,4)) +
          theme(legend.position = "top", panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank())  +
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank(),
        axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.ticks.y=element_blank(), strip.text.x = element_text(size = 12, face="bold")
        )

fig6.a <- ggplot() +
          geom_segment(data=edges, aes(x=FA1.x, y=FA2.x, xend = FA1.y, yend = FA2.y, size=value), colour="grey" ) + 

xlab("FoceAtlas1") +
  ylab("FoceAtlas2") +
                  theme_bw() +
    scale_size( range = c(0.01, 2)) +
        theme(legend.position = "top") +
    geom_text_repel(data = vert.names, colour="black", aes(FA1, FA2), size=2.7, 
    box.padding = unit(1, 'lines'),
     point.padding = 0.5,
    segment.size=0.2,
    max.overlaps=Inf,
    segment.linetype="dashed",
                label=vert.names$cell_type )  +
  
          geom_text(data=vert.names, aes(FA1, FA2, label=cluster, colour=Class ),

                    fontface='bold', size=4) 

fig6.a

library("ggrepel")

ggplot()+
  geom_point(data=total_diff, aes(-DeltaPsi.mean, Probability.mean), alpha=0.1, colour="grey" ) +
  geom_point(data=total_diff[ diff==TRUE, ], aes(-DeltaPsi.mean, Probability.mean, size=-log10(cdf.beta), color=Type), alpha=0.5) +
  ylab("Mean Probability") + 
   xlab("Mean dPSI") +
   # facet_grid(. ~ diff_name) +
  facet_wrap(~   diff_type + diff_name) +
  theme_bw() +
  scale_color_manual (values=gg_color_hue(9), drop=F) +
 theme(legend.position = "top")  +
  ylim(0.5, 1.25) +
  
#  geom_text_repel(data = total_diff[diff==TRUE &  toupper(mgi_symbol) %in% interesting_genes, ],
 #               colour="black", aes(-DeltaPsi.mean, Probability.mean), 
  #              nudge_y      = 0.07,
   #             direction    = "x",
    #            angle        = 90,
     #           vjust        = 1,
      #          segment.size = 0.1,
       #         max.overlaps  = Inf,
        #        label=total_diff[diff==TRUE &  toupper(mgi_symbol) %in% interesting_genes , mgi_symbol] ) 

  
  geom_text_repel(data = total_diff[diff==TRUE &  toupper(mgi_symbol) %in% splicing_regulation, ],
                colour="black", aes(-DeltaPsi.mean, Probability.mean), 
                nudge_y      = 0.07,
                direction    = "x",
                angle        = 90,
                vjust        = 1,
                segment.size = 0.1,
                label=total_diff[diff==TRUE &  toupper(mgi_symbol) %in% splicing_regulation , mgi_symbol] )